Comparison of Kalman Filter and Wavelet Filter for Denoising

Postalcioglu, Seda; Erkan, Kadir; Bolat, Emine Doğru

doi:10.1109/icnnb.2005.1614777

Cited by 17 publications

(10 citation statements)

References 7 publications

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“…The wavelet transform tends to concentrate the signal energy into a relatively small number of coefficients with larger values. This energy-concentrating property makes the wavelet analysis appropriate for signal denoising, estimation, and forecasting (147)(148)(149)(150) and sometimes appears to be more suitable than the widely used Kalman filter (145,151). According to the pertinent literature, there is a tendency to use wavelet filters to filtrate spectroscopic signals because they preserve the characteristics of the peaks.…”

Section: Downloaded By [Stony Brook University] At 00:25 02 November mentioning

confidence: 98%

“…Indeed, the Kalman filter removes disturbances or faults from the signal by using initialization and propagation of error covariance statistics; that is, it computes and propagates the mean and the covariance matrix recursively for a linear system. In distributed systems the computational expense of Kalman filters is thus dominated by the error covariance propagation step, which makes implementation of the Kalman filter impractical in large-scale models (144,145).…”

Section: Downloaded By [Stony Brook University] At 00:25 02 November mentioning

confidence: 99%

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A Review of Signal Enhancement and Noise Reduction Techniques for Tunable Diode Laser Absorption Spectroscopy

Zhao

et al. 2014

Applied Spectroscopy Reviews

138

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Tunable diode laser absorption spectroscopy (TDLAS), as a noninvasive spectroscopic method, permits high-resolution, high-sensitivity, fast, in situ absorption measurements of atomic and molecular species and narrow spectral features in gaseous, solid, and liquid phases. Advances in new diode laser sources and laser spectroscopic techniques generally have triggered an increasing application of TDLAS in various disciplines (for example, atmospheric environmental monitoring, chemical analysis, industrial process control, medical diagnostics and combustion monitoring, etc.) over the last four decades. This article reviews some important developments in TDLAS, from its basic principles as a spectroscopic tool to the demonstration of gas absorption measurements, emphasizing signal enhancement and noise reduction techniques developed for improving current TDLAS performance.

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Section: Downloaded By [Stony Brook University] At 00:25 02 November mentioning

confidence: 98%

Section: Downloaded By [Stony Brook University] At 00:25 02 November mentioning

confidence: 99%

A Review of Signal Enhancement and Noise Reduction Techniques for Tunable Diode Laser Absorption Spectroscopy

Zhao

et al. 2014

Applied Spectroscopy Reviews

138

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“…The technique contains of applying a discrete wavelet transform to the original data. The detail wavelet coefficients are thresholded and inverse transforming the thresholded coefficients to obtain the denoised data [20], [21], [22]. Hard and Soft thresholding methods are generally used for the wavelet coefficients.…”

Section: Fig 2: Db7 Waveletmentioning

confidence: 99%

Online Wavelet Denoising for a Quarter Car Model

Postalcioglu¹

2018

IJCA

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Noise impact cannot be ignored in control system. In online systems when the received data by sensor contains noise, may cause to a problem. Linear position sensor can be widely used to control of body motion in different types of suspension system. Sensor's resolution, accuracy and stability depend on its electronics design. For this purpose, in this paper an online wavelet denoising has been studied for a quarter car model. Vibrations due to the unit step input are controlled with PID controller. If the sensor contains noise, controller performance will be poor. Online wavelet denoising is used to eliminate the noise. Simulation results show that when the system has online wavelet denoising, controller gives better results and system is not affected by the noise. As a result, this type of control strategy can be applied to the semi-active suspension systems to improve driver comfort.

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“…The KF's recursive nature makes its implementation much more feasible than traditional filter [4,14,20], however, in distributed systems, the KF is constrained by large computational expense dominated by the error covariance propagation step which tends to make the implementation of the KF impractical on a large scale [25]. Furthermore, there are no means of correcting past state estimates in linear systems and therefore errors made in the past continue to propagate themselves to subsequent state estimates, hence a disadvantage to KF [19].…”

Section: A) When Is Kf (Not) Considered For Use?mentioning

confidence: 99%

A selective review on target tracking algorithms

Kaawaase

Feng

2011

SPIE Proceedings

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Growing research in computer vision obliges reliable and efficient target tracking methods. This letter proposes a review on target estimation and tracking algorithms grouped into two namely deterministic and nondeterministic based algorithms. Various issues affecting success and/or failure of such algorithms are discussed as well as presenting current references (fifty five in total) on the topic. In conclusion, no single algorithm can be ideal for all tracking problems. It is hoped that with only two groups of tracking and estimation algorithms, this work will guide tracking system designers on choosing a suitable algorithms for use.

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Comparison of Kalman Filter and Wavelet Filter for Denoising

Cited by 17 publications

References 7 publications

A Review of Signal Enhancement and Noise Reduction Techniques for Tunable Diode Laser Absorption Spectroscopy

A Review of Signal Enhancement and Noise Reduction Techniques for Tunable Diode Laser Absorption Spectroscopy

Online Wavelet Denoising for a Quarter Car Model

A selective review on target tracking algorithms

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